Straight answers on budgets, cost drivers, and what to expect at each stage — from a team that builds this software every day.
The short answer: most bespoke AI software projects in the UK cost between £25,000 and £100,000+, delivered over 8 to 16 weeks. The long answer is more useful, because two projects with the same headline description can differ in price by a factor of three. This guide explains why — and how to judge whether a quote is realistic.
At P30X we build bespoke AI systems — process automation, predictive maintenance, computer vision, natural language processing, and custom data platforms — for sectors including lift & elevator, manufacturing, construction, healthcare, logistics, finance, and energy. The figures below reflect what we actually see across those projects.
One well-defined workflow automated end-to-end costs far less than a platform serving several departments. Every extra user role, edge case, and report adds engineering time. Ruthless scoping in discovery is the single biggest lever on price.
AI runs on data. If yours is clean, structured, and accessible, model development is fast. If it lives in spreadsheets, paper records, or a legacy database with no API, expect a data engineering phase before any model is trained — often 15–30% of the budget.
Connecting to a modern ERP or CRM with a documented API is routine. Integrating with ageing on-premise systems, proprietary machinery protocols, or sensor networks takes bespoke connector work — and each integration adds cost and testing time.
Standard machine learning on tabular data is well-trodden ground. Custom computer vision models trained on your specific products, or NLP tuned to your domain language, need data collection, labelling, and validation cycles that push budgets upward.
Cloud-hosted software with standard security is the baseline. Requirements such as on-premise deployment, real-time inference at scale, UK data residency, or healthcare-grade compliance all add infrastructure and audit overhead.
Company size, industry buzzwords, and "AI" in the name. A sensible supplier prices the engineering effort, not the label. If a quote feels priced on your turnover rather than the work, ask for a line-by-line breakdown.
Across a typical 8–16 week project, budget is spent in four broad phases.
Workshops, data audit, feasibility checks, and a fixed-price specification. This is where scope gets locked down and surprises get eliminated.
A working proof of concept on your real data. You see accuracy figures and a usable demo before committing to the full build.
Full development in agile sprints: production models, integrations, interfaces, and testing, with weekly demos so nothing lands as a surprise.
Production launch, monitoring, documentation, and training. Ongoing support and model retraining are then priced separately, typically monthly.
A focused, single-purpose system delivered fast.
A substantial system spanning several workflows or data sources.
Multi-system platforms and demanding environments.
If an off-the-shelf product genuinely fits your workflow, buy it — we'll tell you so in discovery. Build bespoke when the process is your competitive edge, when per-seat licensing compounds painfully, or when no product handles your data, machinery, or sector. Bespoke means you own the asset outright: no per-user fees, no roadmap you can't influence, no vendor lock-in.
The right question isn't "what does it cost?" but "what does it return?" A £40,000 automation that saves two staff-days a week pays for itself inside eighteen months, then keeps saving. A predictive maintenance system is judged against the cost of a single day of unplanned downtime. Before we quote, we model the payback with you — if the numbers don't work, we'll say so.
A suspiciously low quote usually hides one of these: no discovery phase (scope will balloon later as "extras"), no mention of your data quality (the awkward surprises arrive mid-project), vague deliverables ("an AI solution") instead of measurable outcomes, no prototype stage before the full build, and silence on who owns the code and models — with bespoke work, that should be you. A day-rate with no fixed scope is not a price; it's a meter running.
Conversely, a credible quote itemises phases, names the integrations, states accuracy targets, and includes handover and support terms in writing.
Most projects sit between £25,000 and £100,000+. Focused automation tools land at the lower end; multi-system platforms with computer vision, predictive models, or complex integrations sit at the upper end and beyond.
A typical P30X project runs 8 to 16 weeks from discovery to production, depending on scope, data readiness, and the number of systems being integrated.
Up front, yes — but per-user fees run forever and the product rarely fits your workflow exactly. Bespoke costs more initially, but you own it outright and it typically pays back within one to two years for operational use cases.
Broad scope, messy or scattered data, multiple legacy integrations, custom model development, and demanding hosting or compliance requirements are the main multipliers.
Yes — a paid discovery and prototype phase first proves value on one process before you commit to a full build. It de-risks the spend and gives you a working demo for stakeholders.
Tell us what you're trying to achieve and we'll give you an honest, itemised estimate — email [email protected] or call 01299 333446.
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